Stroke is a leading cause of physical disability worldwide. Successful rehabilitation of motor function is critically dependent on the ability to learn to produce coordinated movement. In this project we will investigate the role of the motor cortex and the cerebellum in a form of learning, known as motor adaptation, which has shown to have promising potential for rehabilitation. Adaptation paradigms are extensively used in rehabilitation to promote stroke recovery; some examples are split treadmill belts moving at discordant velocities to entrain cadence, robot-augmented arm training to improve arm coordination, prism adaptation to treat hemispatial neglect, and discordant visual feedback in virtual reality to restore hand function. Numerous meta-analyses and reviews highlight the relatively marginal differences between therapies and the varied capacity for adaptation in patient populations. In order to address the Accelerating the Translation of Preclinical Stroke Research Into Clinical Studies of Stroke Prevention, Acute Treatment, and Recovery and Recovery Translational Research Using Brain-Computer Interface Devices for Stroke and Other Neurological Disorders priorities set forth by the NINDS, and significantly impact the future of adaptation paradigms used for rehabilitation, it is necessary to understand neural machinery of adaptation. Recent work has suggested a physiological link between the cerebellum and motor cortex during adaptation. Other studies, however, have shown that stroke lesions involving primary motor cortex do not affect adaptation. Therefore, the overarching aim of this project is to conduct a focused and novel investigation into two key neural substrates thought to mediate motor adaptation: the cerebellum and motor cortex. Paired pulse transcranial magnetic stimulation techniques will be used to noninvasively track changes in motor cortex intracortical physiology (short intracortical inhibition and intracortical facilitation) and cerebellar modulatio of the motor cortex as subjects learn to adapt to a visuomotor gain perturbation of their finger movement in virtual reality. It is hypothesized that measures of M1 intracortical physiology and cerebellum-motor cortex interactions should track with the reduction of movement error, when explicit information of the perturbation is not provided. The public health relatedness of this project is to explain the unique contributions of cerebellum and M1 to the different phases of learning and pave the way for lesion-specific therapeutic interventions using virtual environments and/or non-invasive brain stimulation.